Merge branch 'main' into int-feat-k8s-readd-sbs-migration-doc

Author: bene2k1

.github/workflows/link-check-schedule.yml

@@ -0,0 +1,12 @@
+name: Check links on schedule
+on:
+  schedule:
+    - cron: "59 23 * * 0" # Runs every Sunday at 23:59 PM
+jobs:
+  linkcheck:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+    - uses: filiph/[email protected]
+      with:
+        arguments: https://www.scaleway.com/en/docs/

ai-data/generative-apis/api-cli/understanding-errors.mdx

@@ -7,7 +7,7 @@ content:
   paragraph: This page explains how to understand errors with Generative APIs
 tags: generative-apis ai-data understanding-data
 dates:
-  validation: 2024-09-02
+  validation: 2024-10-31
   posted: 2024-09-02
 ---
 
@@ -32,6 +32,8 @@ Below are usual HTTP error codes:
 - 404 - **Route Not Found**: The requested resource could not be found. Check your request is being made to the correct endpoint.
 - 422 - **Model Not Found**: The `model` key is present in the request payload, but the corresponding model is not found.
 - 422 - **Missing Model**:  The `model` key is missing from the request payload.
+- 429 - **Too Many Requests**: You are exceeding your current quota for the requested model, calculated in requests per minute. Find rate limits on [this page](/ai-data/generative-apis/reference-content/rate-limits/)
+- 429 - **Too Many Tokens**: You are exceeding your current quota for the requested model, calculated in tokens per minute. Find rate limits on [this page](/ai-data/generative-apis/reference-content/rate-limits/)
 - 500 - **API error**: An unexpected internal error has occurred within Scaleway's systems. If the issue persists, please [open a support ticket](https://console.scaleway.com/support/tickets/create).
 
 For streaming responses via SSE, 5xx errors may occur after a 200 response has been returned.

ai-data/generative-apis/api-cli/using-chat-api.mdx

@@ -56,8 +56,8 @@ Find required headers in [this page](/ai-data/generative-apis/api-cli/using-gene
 
 | Param  | Type | Description |
 | ------------- |-------------|-------------|
-| **messages***     | array of objects     | A list of messages comprising the conversation so far.     |
-| **model***      | string     | The name of the model to query.     |
+| **messages**     | array of objects     | A list of messages comprising the conversation so far.     |
+| **model**      | string     | The name of the model to query.     |
 
 Our chat API is OpenAI compatible. Use OpenAI’s [API reference](https://platform.openai.com/docs/api-reference/chat/create) for more detailed information on the usage.
 
@@ -67,6 +67,7 @@ Our chat API is OpenAI compatible. Use OpenAI’s [API reference](https://platfo
 - top_p
 - max_tokens
 - stream
+- stream_options
 - presence_penalty
 - [response_format](/ai-data/generative-apis/how-to/use-structured-outputs)
 - logprobs
@@ -87,6 +88,6 @@ If you have a use case requiring one of these unsupported parameters, please [co
 
 ## Going further
 
-1. [Python code examples](/ai-data/generative-apis/how-to/query-text-models/#querying-text-models-via-api) to query text models using Scaleway's Chat API.
+1. [Python code examples](/ai-data/generative-apis/how-to/query-language-models/#querying-language-models-via-api) to query text models using Scaleway's Chat API
 2. [How to use structured outputs](/ai-data/generative-apis/how-to/use-structured-outputs) with the `response_format` parameter
 3. [How to use function calling](/ai-data/generative-apis/how-to/use-function-calling) with `tools` and `tool_choice`

ai-data/generative-apis/api-cli/using-embeddings-api.mdx

@@ -40,8 +40,8 @@ Find required headers in [this page](/ai-data/generative-apis/api-cli/using-gene
 
 | Param  | Type | Description |
 | ------------- |-------------|-------------|
-| **input***     | string or array     | Input text to embed, encoded as a string or array of strings. It cannot be an empty string.  |
-| **model***      | string     | The name of the model to query.     |
+| **input**      | string or array     | Input text to embed, encoded as a string or array of strings. It cannot be an empty string.  |
+| **model**       | string     | The name of the model to query.     |
 
 Our embeddings API is OpenAI compatible. Use OpenAI’s [API reference](https://platform.openai.com/docs/api-reference/embeddings) for more detailed information on the usage.
 

ai-data/generative-apis/api-cli/using-generative-apis.mdx

@@ -13,7 +13,6 @@ dates:
 
 ## Access
 
-- Access to this service is restricted while in beta. You can request access to the product by filling out a form on the Scaleway's [betas page](https://www.scaleway.com/en/betas/#generative-apis).
 - A valid [API key](/identity-and-access-management/iam/how-to/create-api-keys/) is needed.
 
 ## Authentication

ai-data/generative-apis/how-to/query-code-models.mdx

@@ -0,0 +1,62 @@
+---
+meta:
+  title: How to query code models
+  description: Learn how to interact with powerful language models specialized in code using Scaleway's Generative APIs service.
+content:
+  h1: How to query code models
+  paragraph: Learn how to interact with powerful language models specialized in code using Scaleway's Generative APIs service.
+tags: generative-apis ai-data language-models code-models chat-completions-api
+dates:
+  validation: 2024-12-09
+  posted: 2024-12-09
+---
+
+Scaleway's Generative APIs service allows users to interact with powerful code models hosted on the platform.
+
+Code models are inherently [language models](/ai-data/generative-apis/how-to/query-language-models/) specialized in **understanding code**, **generating code** and **fixing code**. 
+
+As such, they will be available through the same interfaces as language models:
+- The Scaleway [console](https://console.scaleway.com) provides complete [playground](/ai-data/generative-apis/how-to/query-language-models/#accessing-the-playground), aiming to test models, adapt parameters, and observe how these changes affect the output in real-time.
+- Via the [Chat API](/ai-data/generative-apis/how-to/query-language-models/#querying-language-models-via-api)
+
+For more information on how to query language models, read [our dedicated documentation](/ai-data/generative-apis/how-to/query-language-models/).
+
+Code models are also ideal AI assistants when **added to IDEs** (integrated development environments). 
+
+<Macro id="requirements" />
+
+- A Scaleway account logged into the [console](https://console.scaleway.com)
+- [Owner](/identity-and-access-management/iam/concepts/#owner) status or [IAM permissions](/identity-and-access-management/iam/concepts/#permission) allowing you to perform actions in the intended Organization
+- A valid [API key](/identity-and-access-management/iam/how-to/create-api-keys/) for API authentication
+- An IDE such as Visual Studio Code or JetBrains
+
+## Install Continue in your IDE
+
+[Continue](https://www.continue.dev/) is an [open-source code assistant](https://github.com/continuedev/continue) to connect AI models to your IDE.
+
+To get Continue, simply hit `install` in your IDE's marketplace:
+- [Visual Studio Marketplace](https://marketplace.visualstudio.com/items?itemName=Continue.continue)
+- [JetBrains Marketplace](https://plugins.jetbrains.com/plugin/22707-continue)
+
+## Configure Scaleway as an API provider in Continue
+
+Continue's `config.json` file will set models and providers allowed for chat, autocompletion etc.
+Here is an example configuration with Scaleway's OpenAI-compatible provider:
+
+```json
+"models": [
+    {
+      "model": "qwen2.5-coder-32b-instruct",
+      "title": "Qwen2.5-coder",
+      "provider": "scaleway",
+      "apiKey": "###SCW SECRET KEY###"
+    }
+]
+```
+
+<Message type="tip">
+ The config.json file is typically stored as `~/.continue/config.json` on Linux/macOS systems, and `%USERPROFILE%\.continue\config.json` on Windows.
+</Message>
+
+Read more about how to set up your `config.json` on the [official Continue documentation](https://docs.continue.dev/reference).
+

ai-data/generative-apis/how-to/query-embedding-models.mdx

@@ -5,9 +5,9 @@ meta:
 content:
   h1: How to query embedding models
   paragraph: Learn how to interact with embedding models using Scaleway's Generative APIs service.
-tags: generative-apis ai-data embedding-models
+tags: generative-apis ai-data embedding-models embeddings-api
 dates:
-  validation: 2024-08-28
+  validation: 2024-10-30
   posted: 2024-08-28
 ---
 
@@ -18,7 +18,6 @@ The embedding service is OpenAI compatible. Refer to OpenAI's [embedding documen
 
 <Macro id="requirements" />
 
-- Access to this service is restricted while in beta. You can request access to the product by filling out a form on Scaleway's [betas page](https://www.scaleway.com/en/betas/#generative-apis).
 - A Scaleway account logged into the [console](https://console.scaleway.com)
 - [Owner](/identity-and-access-management/iam/concepts/#owner) status or [IAM permissions](/identity-and-access-management/iam/concepts/#permission) allowing you to perform actions in the intended Organization
 - A valid [API key](/identity-and-access-management/iam/how-to/create-api-keys/) for API authentication
@@ -51,22 +50,22 @@ client = OpenAI(
 )
 ```
 
-### Generating embeddings with sentence-t5-xxl
+### Generating embeddings with bge-multilingual-gemma2
 
-You can now generate embeddings using the `sentence-t5-xxl` model, such as the following example:
+You can now generate embeddings using the `bge-multilingual-gemma2` model, such as the following example:
 
 ```python
-# Generate embeddings using the 'sentence-t5-xxl' model
+# Generate embeddings using the 'bge-multilingual-gemma2' model
 embedding_response = client.embeddings.create(
     input= "Artificial Intelligence is transforming the world.",
-    model= "sentence-t5-xxl"
+    model= "bge-multilingual-gemma2"
 )
 
 # Output the embedding vector
 print(embedding_response.data[0].embedding)
 ```
 
-This code sends input text to the `sentence-t5-xxl` embedding model and returns a vector representation of the text. The `sentence-t5-xxl` model is specifically designed for generating high-quality sentence embeddings.
+This code sends input text to the `bge-multilingual-gemma2` embedding model and returns a vector representation of the text. The `bge-multilingual-gemma2` model is specifically designed for generating high-quality sentence embeddings.
 
 ### Model parameters and their effects
 

ai-data/generative-apis/how-to/query-text-models.mdx renamed to ai-data/generative-apis/how-to/query-language-models.mdx

@@ -1,35 +1,45 @@
 ---
 meta:
-  title: How to query text models
-  description: Learn how to interact with powerful text models using Scaleway's Generative APIs service.
+  title: How to query language models
+  description: Learn how to interact with powerful language models using Scaleway's Generative APIs service.
 content:
-  h1: How to query text models
-  paragraph: Learn how to interact with powerful text models using Scaleway's Generative APIs service.
-tags: generative-apis ai-data text-models
+  h1: How to query language models
+  paragraph: Learn how to interact with powerful language models using Scaleway's Generative APIs service.
+tags: generative-apis ai-data language-models chat-completions-api
 dates:
-  validation: 2024-08-28
+  validation: 2024-10-30
   posted: 2024-08-28
 ---
 
-Scaleway's Generative APIs service allows users to interact with powerful text models hosted on the platform.
+Scaleway's Generative APIs service allows users to interact with powerful language models hosted on the platform.
 
-There are several ways to interact with text models:
-- The Scaleway [console](https://console.scaleway.com) will soon provide a complete [playground](/ai-data/generative-apis/how-to/query-text-models/#accessing-the-playground), aiming to test models, adapt parameters, and observe how these changes affect the output in real-time.
-- Via the [Chat API](/ai-data/generative-apis/how-to/query-text-models/#querying-text-models-via-api)
+There are several ways to interact with language models:
+- The Scaleway [console](https://console.scaleway.com) provides complete [playground](/ai-data/generative-apis/how-to/query-language-models/#accessing-the-playground), aiming to test models, adapt parameters, and observe how these changes affect the output in real-time.
+- Via the [Chat API](/ai-data/generative-apis/how-to/query-language-models/#querying-language-models-via-api)
 
 <Macro id="requirements" />
 
-- Access to this service is restricted while in beta. You can request access to the product by filling out a form on Scaleway's [betas page](https://www.scaleway.com/en/betas/#generative-apis).
 - A Scaleway account logged into the [console](https://console.scaleway.com)
 - [Owner](/identity-and-access-management/iam/concepts/#owner) status or [IAM permissions](/identity-and-access-management/iam/concepts/#permission) allowing you to perform actions in the intended Organization
 - A valid [API key](/identity-and-access-management/iam/how-to/create-api-keys/) for API authentication
 - Python 3.7+ installed on your system
 
 ## Accessing the Playground
 
-Scaleway's Playground is in development, stay tuned!
+Scaleway provides a web playground for instruct-based models hosted on Generative APIs.
 
-## Querying text models via API
+1. Navigate to **Generative APIs** under the **AI** section of the [Scaleway console](https://console.scaleway.com/) side menu. The list of models you can query displays.
+2. Click the name of the chat model you want to try. Alternatively, click <Icon name="more" /> next to the chat model, and click **Try model** in the menu. 
+
+The web playground displays.
+
+## Using the playground
+1. Enter a prompt at the bottom of the page, or use one of the suggested prompts in the conversation area.
+2. Edit the hyperparameters listed on the right column, for example the default temperature for more or less randomness on the outputs. 
+3. Switch models at the top of the page, to observe the capabilities of chat models offered via Generative APIs. 
+4. Click **View code** to get code snippets configured according to your settings in the playground.
+
+## Querying language models via API
 
 The [Chat API](/ai-data/generative-apis/api-cli/using-chat-api/) is an OpenAI-compatible REST API for generating and manipulating conversations.
 
@@ -129,7 +139,7 @@ response = client.chat.completions.create(
 )
 
 for chunk in response:
-    if chunk.choices[0].delta.content:
+    if chunk.choices and chunk.choices[0].delta.content:
         print(chunk.choices[0].delta.content, end="")
 ```
 
@@ -157,7 +167,8 @@ async def main():
         stream=True,
     )
     async for chunk in stream:
-        print(chunk.choices[0].delta.content, end="")
+        if chunk.choices and chunk.choices[0].delta.content:
+            print(chunk.choices[0].delta.content, end="")
 
 asyncio.run(main())
 ```